--- layout: post title: Continuing with R excerpt: These slides will be presented at the DSCOE Inferno Lite and are intended to give an idea of how to continue with R after an introductory course. --- DSCOE Inferno Lite

DSCOE Inferno Lite

Ian Kloo

August 2016

Why continue with R?

Re-usable Code

  • Write it once, use it forever
  • Share with others to avoid duplicate effort

Auditable Methods

  • Easy to see what you did (assumptions)
  • Can easily tweak analyses without re-doing everything
  • Avoids the “hit by a bus” problem

Huge and Growing Community

  • Open source breeds collaboration
  • Any question has probably already been asked or answered
  • Ongoing development guaranteed

What can/should I do Now?

Advanced Modeling

Statistical Methods

Machine Learning

  • caret package!

Visualizations

ggplot

  • Publication-ready (with some work)
  • Easy syntax
  • Lots of support

ggplot: scientific

ggplot: maps

ggplot: heatmaps

ggplot: anything!

Pre-built htmlwidgets

  • rCharts, networkD3, plotly, leaflet, and many more!
  • Interactive visualizations
  • No need to learn javascript
  • Somewhat difficult to customize (in some cases)

rCharts

Plotly

Leaflet

Sigma

Roll-Your-Own htmlwidgets

  • Extremely customizable and interactive
  • Javascript knowledge required
  • Can write the JS once, then use R!
  • Add javascript visualizations to presentation, applications, and papers
  • Difficult learning curve

forceMap

Get a Project!

  • R is like running - stop for a few weeks and you lose most of it
  • Quick-turn work projects may not work, but try to use R if possible
  • Find something you are interested in and work at home

App Development

Monitoring Media Narratives

ANC Planning Tool

Resources

DSCOE

R Bloggers

Stackoverflow

R Studio Tutorials

Kaggle